The Transit Opportunity Index (TOI), developed by Mamun et al. (2013), combines measures of spatial and temporal accessibility with measures of connectivity to capture the opportunity offered to transit passengers in a zone. TOI measures access to public transportation services and infrastructure, rather than access to particular destinations. In the original paper, Mamun et al. (2013) calculated TOI for the relatively small city of New Haven, Connecticut, USA. Due to the small size of the study area, the authors calculate TOI manually. For larger analysis areas, however, calculating TOI in a reasonable amount of time requires machine-readable datasets and necessitates automated algorithms for data processing. One of the primary purposes of the research presented in this paper is to develop the algorithms necessary to calculate TOI for larger analysis areas, a non-trivial task considering the substantial memory requirements of the calculations. The automated tool created in this research is able to calculate TOI values for large metropolitan areas, including Boston, substantially faster than the authors of the original paper were able to calculate TOI values for the much smaller city of New Haven using the original method.